—A major assumption in many machine learning and data mining algorithms is that the training and future data must be in the same feature space and have the same distribution. How...
As a result of the recent explosion of sensor-equipped mobile phone market, the phenomenal growth of Internet and social network users, and the large deployment of sensor network i...
The frequent items problem is to process a stream of items and find all items occurring more than a given fraction of the time. It is one of the most heavily studied problems in d...
Trajectory prediction (TP) of moving objects has grown rapidly to be a new exciting paradigm. However, existing prediction algorithms mainly employ kinematical models to approximat...
— The paper presents an approach that combines conceptual and evolutionary techniques to support change impact analysis in source code. Information Retrieval (IR) is used to deri...
Huzefa H. Kagdi, Malcom Gethers, Denys Poshyvanyk,...